A Quick Guide for Enterprise Data Strategy

Are you experiencing problems with cluttered, lost, and unsynchronized data? Ripple has you covered with a guide to managing your company's data. Enterprise Data Strategy was created to solve scenarios where users within organizations source, manage, and store data independently. Data conflicts and quality discrepancies can result from uncoordinated efforts by multiple company segments, diminishing the data's credibility as it is used for operations and reporting. Without a systematic way, it will be chaotic and will lose time, effort, and revenue. This article will help you push your strategy development process to the next level.





What is Enterprise Data Strategy?

Enterprise Data Strategy (EDS) refers to an organization's ability to precisely describe, conveniently integrate, and effectively retrieve data for internal and external applications.


Why is Enterprise Data Strategy important?

The purpose of an enterprise data strategy is to instill trust in data assets. It aims at producing data that is accurate, consistent, transparent and relies on data precision.


Basic Concepts in Enterprise Data Strategy

This simple acronym, ADHOC, is the overall model for the company's enterprise data strategy.

  • Accomplish clear data management protocols and processes to accelerate data integration, usability, visibility, and access.

  • Defining the company's goals will guide the data strategy and actions, strengthening data management skills.

  • Having good data accessibility facilitates collaboration across various departments within a company.

  • Observe how data is collected and figure out a means to store it so that the team can discover and get the information without duplicating it.

  • Create standards for naming data elements and generate data values to make your data more efficient, shareable, and usable.

Executing Enterprise Data Strategy

Ripple presents five basic steps to create a simple enterprise data strategy scheme for your company:

  1. Form a data management team. Select individuals who are experienced with data-related processes. They will assist in implementing the data strategy and oversee allocating resources, creating policies, dealing with data-related issues, and other things.

  2. Establish clear objectives. Deciding on quantifiable targets is an important aspect of developing a data strategy. Long-term and short-term goals, overarching and specific objectives, should all be established. Finally, your data should assist you in achieving your overall business objectives.

  3. Determine where and how data will be acquired. The business objectives dictate the kinds of data required. The company's goal might be to target online ads to obtain new clients for your company. It may achieve this by collecting demographic information from clients who visit and purchase things on the company website. Tracking these targeted ads will make it easier for the company to determine which ads are effective and not.

  4. Produce a data strategy map. Devise a strategy for achieving them and will serve as the foundation for your data strategy map. These plans should be detailed and include how the company uses the data, the personalization of content, the goal's target, what procedure and technology will be used, how long and much it will cost, and the outcome. The data strategy roadmap will detail how you intend to accomplish your objectives.

  5. Build a data storage and organization strategy. Policies for data storage and organization should be included in your data strategy. These elements of data management are critical because they influence how actionable and shareable your data is. When planning your storage strategy, think about how much storage capacity you will need and how your storage strategy will affect data sharing and usage. How you organize your data impacts how simple it is to obtain, analyze, and use. Different ways may work well for different businesses, but in general, you should keep your data in a system that is easy to access and that follows a standard structure.

After all these steps are undertaken, implementing an enterprise data strategy will be effortless. You would be surprised with the results you would get if you planned and executed them carefully. Likewise, your company will thank you for efficient and organized data.


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